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Best of LinkedIn: Artificial Intelligence CW 35/ 36 · Best of LinkedIn: Digital Transformation & Tech

• 0:00
  Speaker 1: This deep dive is provided by Thomas Allgaier and Frennis, based on the most relevant LinkedIn posts about artificial intelligence in calendar weeks thirty-five and thirty-six.
• 0:10
  Speaker 1: Frennis supports enterprises with market and competitive intelligence, decoding emerging technologies, customer insights, regulatory shifts, and competitor strategies.
• 0:20
  Speaker 1: So product teams and strategy leaders don't just react, but shape the future of AI.
• 0:25
  Speaker 1: Welcome to the deep dive.
• 0:27
  Speaker 1: Look, if you've been on LinkedIn lately, you know.
• 0:29
  Speaker 1: It's just... a wash with AI content, an absolute flood.
• 0:33
  Speaker 0: Oh, completely overwhelming,
• 0:34
  Speaker 1: yeah.
• 0:34
  Speaker 1: So our mission today is really to cut through all that noise for you.
• 0:38
  Speaker 0: Absolutely.
• 0:39
  Speaker 0: Think of us as, well, your curators.
• 0:41
  Speaker 0: We've sifted through everything from calendar weeks, thirty-five and thirty-six, to find the really key top artificial intelligence trends seen across LinkedIn.
• 0:50
  Speaker 1: Distilling it down for you, especially if you're in the ICT and tech industry, giving you those crucial insights.
• 0:55
  Speaker 1: Exactly.
• 0:55
  Speaker 0: We want to help you stay ahead of the curve.
• 0:57
  Speaker 1: We'll be touching on, you know, big strategic shifts.
• 0:59
  Speaker 1: what these AI agents actually are, the whole governance piece, market feelings, all of it.
• 1:03
  Speaker 0: It's about helping you shape what's next, not just react to it.
• 1:07
  Speaker 1: Okay, let's kick things off with theme one, strategy and operating models.
• 1:12
  Speaker 1: How companies are really having to rethink things at a core level because of AI?
• 1:18
  Speaker 0: Yeah, it feels like we're past the purely theoretical stage now.
• 1:22
  Speaker 1: Definitely.
• 1:23
  Speaker 1: It's getting practical and sometimes painful, right?
• 1:25
  Speaker 0: Precisely.
• 1:26
  Speaker 0: And Daniel Paul had a great point on this.
• 1:28
  Speaker 0: He said, More frameworks won't save your agent.
• 1:31
  Speaker 0: A clear roadmap
• 1:32
  Speaker 1: will.
• 1:33
  Speaker 1: That rings true.
• 1:34
  Speaker 0: It does, because so many companies, they stumble, they don't know where to start, they jump between things.
• 1:39
  Speaker 1: And it just leads to chaos.
• 1:41
  Speaker 0: Total chaos.
• 1:42
  Speaker 0: And then they give up.
• 1:43
  Speaker 0: So that clear, strategic approach, it's just non-negotiable now.
• 1:47
  Speaker 1: Absolutely.
• 1:47
  Speaker 1: And, you know, Alina Keck shared this, frankly, staggering statistic from MIT.
• 1:52
  Speaker 1: Oh, yeah.
• 1:53
  Speaker 1: Ninety-five percent of generative AI projects failing to drive revenue.
• 1:58
  Speaker 1: ninety-five percent
• 1:59
  Speaker 0: huge
• 2:00
  Speaker 1: and often it's because they lead with the tech the shiny object not with a real solid business problem.
• 2:05
  Speaker 0: you have to ask what are we actually solving here?
• 2:08
  Speaker 0: first exact which you know connects to what chris kimmel is saying about finding your north star.
• 2:12
  Speaker 0: before you even think about ai governance policies.
• 2:15
  Speaker 1: right you need that strategic alignment first otherwise the policies are just floating disconnected precisely and it's changing leadership to isn't it?
• 2:23
  Speaker 1: matthew?
• 2:24
  Speaker 1: a mattson had this interesting idea moving from managing people to orchestrating AI systems.
• 2:33
  Speaker 0: Orchestrating, I like that.
• 2:34
  Speaker 1: Yeah, it's not about micromanaging.
• 2:36
  Speaker 1: the AI's choices, but designing the system itself, you know, with ethics, autonomy, intent, build right in.
• 2:42
  Speaker 0: It's a fundamental shift in what leadership looks like.
• 2:45
  Speaker 0: And Jens Bucking talked about these frontier firms.
• 2:47
  Speaker 1: Ah, yes, the frontier firms.
• 2:49
  Speaker 0: Yes, structured around on-demand intelligence, human AI teams working together, super agile.
• 2:54
  Speaker 0: He argues this isn't just nice to have anymore.
• 2:57
  Speaker 1: It's becoming a survival imperative.
• 2:59
  Speaker 0: That's the phrase he used, survival imperative.
• 3:02
  Speaker 1: So pulling that all together.
• 3:04
  Speaker 1: The big takeaway for leaders it seems like it's disciplined investment really tracking the value and Well fundamentally rethinking how work gets done.
• 3:13
  Speaker 1: Yep
• 3:14
  Speaker 0: caution against the hype focus on the value.
• 3:16
  Speaker 1: Okay now Let's get into AI agents.
• 3:20
  Speaker 1: This is where it gets really interesting.
• 3:21
  Speaker 1: I think feels like a major leap.
• 3:23
  Speaker 0: Oh, absolutely.
• 3:24
  Speaker 0: This is way beyond just simple automation.
• 3:27
  Speaker 0: Richard Lefebvre defined agentic AI really well.
• 3:30
  Speaker 1: How do you put it
• 3:32
  Speaker 0: as systems that can autonomously execute workflows?
• 3:35
  Speaker 0: crucially correct their own errors and adapt strategies.
• 3:39
  Speaker 0: He said they act more like a colleague than a calculator.
• 3:42
  Speaker 1: A colleague, not a calculator.
• 3:43
  Speaker 1: I like that framing.
• 3:44
  Speaker 0: Yeah.
• 3:44
  Speaker 0: And he gave those great examples.
• 3:45
  Speaker 0: You know, the evolution from Wally, the tireless steward to R-to-D to the problem solver, and then to Jarvis, the sort of strategic augmenter.
• 3:55
  Speaker 0: It shows that path towards intelligence that really enhances what we can do.
• 3:59
  Speaker 1: Makes it very tangible.
• 4:00
  Speaker 1: And these aren't just sci-fi concepts now.
• 4:02
  Speaker 1: Alex's Cova claimed businesses using these agents, growing twice as fast.
• 4:06
  Speaker 0: Two times faster, wow.
• 4:08
  Speaker 0: Yeah.
• 4:08
  Speaker 1: Siting examples like lead gen agents, sales outreach, content creation, even competitive intelligence.
• 4:14
  Speaker 1: And they can be built relatively quickly, in weeks, apparently.
• 4:17
  Speaker 0: So real business value right now.
• 4:18
  Speaker 1: Exactly.
• 4:19
  Speaker 1: And Jake Jones added another layer talking about how agents tackle operational friction.
• 4:24
  Speaker 0: Operational friction, the work between the work.
• 4:27
  Speaker 0: That's
• 4:27
  Speaker 1: it.
• 4:28
  Speaker 1: Triaging requests, gathering info.
• 4:31
  Speaker 1: All that messy stuff that bogs teams down, not just automating single tasks, but smoothing the whole flow.
• 4:37
  Speaker 0: Reducing the chaos.
• 4:39
  Speaker 0: That's huge.
• 4:40
  Speaker 1: But we need some caution here too.
• 4:43
  Speaker 1: Sure.
• 4:43
  Speaker 1: Michael Short pointed out the term AI agent implies agency responsibility.
• 4:48
  Speaker 0: Yeah, which current tools don't really have.
• 4:50
  Speaker 0: Human accountability is still absolutely central.
• 4:52
  Speaker 0: We can't forget that.
• 4:53
  Speaker 1: Good point.
• 4:54
  Speaker 1: And Blake Oliver made a useful distinction between like linear AI workflows and true AI agents that have goals and autonomy.
• 5:02
  Speaker 1: Right,
• 5:02
  Speaker 0: but he also mentioned their limits, like terrible memories, context window issues.
• 5:07
  Speaker 0: They're powerful, but not magic.
• 5:09
  Speaker 1: Still limitations to work around.
• 5:11
  Speaker 1: For sure.
• 5:12
  Speaker 1: So this all points towards a pretty massive shift in how we work.
• 5:15
  Speaker 1: Gustavo Valbuena called it the agentic era.
• 5:18
  Speaker 0: The agentic era.
• 5:19
  Speaker 0: makes sense.
• 5:19
  Speaker 0: And
• 5:19
  Speaker 1: a lot of Brickner said HR needs to start planning now.
• 5:22
  Speaker 1: How do you onboard manage, integrate AI agents into the workforce?
• 5:25
  Speaker 0: Yeah, like hiring a whole new... type of team member almost, fascinating implications for HR.
• 5:30
  Speaker 0: Okay,
• 5:31
  Speaker 1: let's pivot slightly.
• 5:32
  Speaker 1: How is all this AI actually showing up in new products, new platforms, changing how we interact with tech day to day?
• 5:40
  Speaker 0: Well, one interesting thing was Dan Williams breaking down data bricks, agent bricks.
• 5:44
  Speaker 1: Agent bricks, okay.
• 5:45
  Speaker 1: Yeah,
• 5:45
  Speaker 0: the promises you pointed out your documents and boom, you get a working AI agent.
• 5:49
  Speaker 0: Pretty cool.
• 5:50
  Speaker 0: But he noted you need the right setup.
• 5:53
  Speaker 0: Ah, the catch.
• 5:54
  Speaker 0: Always a catch needs their unity catalog, that data governance piece and serverless compute.
• 5:59
  Speaker 0: So specific requirements.
• 6:00
  Speaker 1: Got it.
• 6:01
  Speaker 1: And on the creative side, I saw pretty hectic deep dive on Google's nano banana.
• 6:07
  Speaker 1: Sounds funny.
• 6:08
  Speaker 1: but looks
• 6:08
  Speaker 0: powerful.
• 6:09
  Speaker 0: Banana banana, tell me more.
• 6:11
  Speaker 1: It's an image editing model.
• 6:12
  Speaker 1: Does things like identity preservation, prompt to pixel pipeline.
• 6:16
  Speaker 1: It really seems like the future for creative work, making complex editing much more intuitive.
• 6:20
  Speaker 1: Very cool.
• 6:21
  Speaker 1: And Elliot Boreffa had some good advice too saying, great AI content isn't magic.
• 6:26
  Speaker 1: It's about high quality training data, good references, getting beyond just generic stuff.
• 6:30
  Speaker 0: Quality in, quality out, still applies.
• 6:33
  Speaker 1: Absolutely.
• 6:34
  Speaker 0: And speaking of interaction changes, Robert Stupak had this pretty provocative take on search.
• 6:41
  Speaker 1: Oh, yeah.
• 6:41
  Speaker 0: He sees us moving from SEO, you know, search engine optimization to Genio, generative engine optimization.
• 6:48
  Speaker 1: Genio, okay.
• 6:49
  Speaker 0: And shifting from browsing websites to a gentic commerce.
• 6:52
  Speaker 0: He even floated the idea that AI overviews in chat could mean, well, the end of websites.
• 6:59
  Speaker 0: Whoa.
• 7:00
  Speaker 1: The end of websites.
• 7:01
  Speaker 1: That is bold.
• 7:02
  Speaker 0: It's a big thought, right?
• 7:03
  Speaker 0: It changes how we access everything online.
• 7:05
  Speaker 1: Definitely food for thought.
• 7:07
  Speaker 1: And more practically.
• 7:08
  Speaker 1: Martin Crowley had a guide on picking AI video tools like Google, VO-II, Sora, Runway.
• 7:14
  Speaker 1: Yeah,
• 7:14
  Speaker 0: based on quality, speed, what you need it for.
• 7:16
  Speaker 0: His point was, don't just stick to one.
• 7:18
  Speaker 1: Makes sense.
• 7:18
  Speaker 1: And Rachelle Schmerzel talked about using our retrieval augmented generation.
• 7:22
  Speaker 0: Ah, REG, combining generative AI with real-time data.
• 7:26
  Speaker 1: Exactly.
• 7:26
  Speaker 1: For virtual agents and contact centers.
• 7:29
  Speaker 1: Making them way more accurate by pulling in live business info.
• 7:32
  Speaker 0: Super useful application.
• 7:33
  Speaker 1: Okay, let's zoom out a bit now.
• 7:35
  Speaker 1: Look at the bigger picture.
• 7:37
  Speaker 1: The partnerships, the ecosystem moves, what's happening regionally.
• 7:40
  Speaker 0: Yeah, there's some significant moves there.
• 7:42
  Speaker 0: Mark Calder had reported on Broadcom partnering with OpenAI.
• 7:45
  Speaker 1: To design AI accelerator chips, right?
• 7:47
  Speaker 0: Exactly.
• 7:48
  Speaker 0: That's a big deal.
• 7:49
  Speaker 0: Puts them right in the ring within video, basically.
• 7:53
  Speaker 0: Shows hardware is becoming this co-developed thing.
• 7:55
  Speaker 1: Interesting.
• 7:56
  Speaker 1: And in fintech.
• 7:57
  Speaker 1: Oh.
• 7:58
  Speaker 1: Seemed like a lot going on.
• 7:59
  Speaker 1: Oh,
• 7:59
  Speaker 0: yeah.
• 8:00
  Speaker 0: Linus Biliunas and Simon Taylor flagged a bunch of stuff.
• 8:04
  Speaker 0: AI powered digital banks like Right Bank, New Bank Expanding, Gemini's new XRP card.
• 8:10
  Speaker 1: And Visa dropping its agentic commerce APIs, which was notable.
• 8:14
  Speaker 1: Right.
• 8:15
  Speaker 0: Shows how fast things are moving and shifting in finance tech.
• 8:18
  Speaker 0: Definitely.
• 8:18
  Speaker 0: And connecting that globally, Dr.
• 8:20
  Speaker 0: Stefan Samble highlighted what's happening in Europe, specifically the IPAI project in Germany.
• 8:25
  Speaker 0: The
• 8:26
  Speaker 1: Dieter Schwartz Foundation thing.
• 8:27
  Speaker 0: That's the one in Heilbronn.
• 8:29
  Speaker 0: being called Europe's most ambitious supplied AI project.
• 8:32
  Speaker 0: Really trying to bridge research and actual application.
• 8:35
  Speaker 0: Plus
• 8:35
  Speaker 1: they just launched Jupiter, right?
• 8:37
  Speaker 1: Europe's fastest supercomputer.
• 8:39
  Speaker 0: Yep.
• 8:39
  Speaker 0: So real push for, you know, European AI capability and maybe sovereignty.
• 8:44
  Speaker 0: And
• 8:45
  Speaker 1: it's not just business and research.
• 8:46
  Speaker 1: AI is expanding into defense too.
• 8:48
  Speaker 1: Yuri Jackson have mentioned a Finnish company, Kelu.
• 8:51
  Speaker 0: With the autonomous hydrogen airship.
• 8:53
  Speaker 0: Yeah, participating in a NATO exercise.
• 8:55
  Speaker 1: Shows AI's reach.
• 8:57
  Speaker 1: and Borigurr appointed to the Smart AI twenty-twenty-five event, focusing purely on industrial AI, cognitive robotics, smart manufacturing.
• 9:06
  Speaker 0: So the ecosystem is really branching out everywhere, every sector.
• 9:09
  Speaker 1: So, okay, let's bring it back down to Earth.
• 9:12
  Speaker 1: What does this all mean for day-to-day operations?
• 9:14
  Speaker 1: Let's dive into some real-world adoption examples.
• 9:17
  Speaker 1: Use cases.
• 9:17
  Speaker 0: Yeah, good idea.
• 9:19
  Speaker 0: Shri Elaprolou shared a fantastic AI for good example from Buenos Aires.
• 9:23
  Speaker 1: Boti, their city assistant.
• 9:24
  Speaker 0: Exactly.
• 9:25
  Speaker 0: Using a gentic AI land graph, Amazon Bedrock to handle millions of citizen conversations a month.
• 9:30
  Speaker 0: accurate culturally relevant responses.
• 9:33
  Speaker 0: Really impressive stuff.
• 9:34
  Speaker 1: That is impactful.
• 9:35
  Speaker 1: Oh.
• 9:35
  Speaker 1: And maybe closer to home for some listeners, Varun Rana, noted the New York subway is adopting agentic AI.
• 9:41
  Speaker 0: For efficiency, yeah.
• 9:42
  Speaker 0: He had that funny line.
• 9:43
  Speaker 1: MTA, but the A stands for agentic.
• 9:45
  Speaker 1: Yeah.
• 9:46
  Speaker 1: It shows even, you know, traditional public infrastructure is getting on board.
• 9:49
  Speaker 0: Definitely.
• 9:50
  Speaker 0: And in banking, Vidya Vargavan wrote about using AI for frictionless, personalized services.
• 9:56
  Speaker 0: She mentioned a FAST framework.
• 9:58
  Speaker 1: Frictionless?
• 9:59
  Speaker 1: adaptive, secure, transparent.
• 10:02
  Speaker 0: That's it!
• 10:03
  Speaker 0: Moving towards proactive guidance, not just transactions.
• 10:06
  Speaker 1: And healthcare.
• 10:06
  Speaker 1: Wow, lots happening there.
• 10:08
  Speaker 0: Seems like it.
• 10:09
  Speaker 1: Dr.
• 10:09
  Speaker 1: Joachim H. shared how InfectoFarm built generative AI in-house.
• 10:15
  Speaker 1: Proving pharma can do it themselves.
• 10:17
  Speaker 1: Robert Perl highlighted how AI tools are empowering patients, changing that doctor-patient dynamic.
• 10:23
  Speaker 1: Making
• 10:23
  Speaker 0: it more collaborative.
• 10:24
  Speaker 0: Yeah.
• 10:25
  Speaker 1: And John Baker had this really counterintuitive finding.
• 10:28
  Speaker 1: healthcare workers who embrace the paradoxes around AI.
• 10:31
  Speaker 1: They actually adopt it more and are happier with it.
• 10:33
  Speaker 0: Interesting psychological angle there.
• 10:35
  Speaker 0: Isn't
• 10:35
  Speaker 1: it?
• 10:36
  Speaker 1: And maybe the biggest news.
• 10:38
  Speaker 1: Ravichandran Subya reported Russia is starting human trials for an AI made cancer vaccine.
• 10:42
  Speaker 1: A
• 10:42
  Speaker 0: cancer vaccine designed by AI.
• 10:45
  Speaker 0: That's potentially revolutionary.
• 10:46
  Speaker 0: It's truly
• 10:47
  Speaker 1: groundbreaking if it pans out.
• 10:49
  Speaker 0: And let's not forget HR.
• 10:50
  Speaker 0: Some year Pinocchalapatti's podcast was asking big questions.
• 10:55
  Speaker 0: How will agents change recruitment?
• 10:57
  Speaker 0: Rejecting candidates.
• 10:59
  Speaker 0: Predicting quits.
• 11:01
  Speaker 0: What is the recruiter of twenty thirty?
• 11:03
  Speaker 1: Yeah, HR seems ripe for this agentic shift.
• 11:06
  Speaker 1: But despite all these amazing examples, Martinez Nicolaeva threw a bit of cold water on things.
• 11:11
  Speaker 1: He's skeptical about the high adoption rates we hear about.
• 11:14
  Speaker 1: Oh, why is that?
• 11:15
  Speaker 1: He thinks many businesses are just scratching the surface.
• 11:18
  Speaker 1: You know, using AI for basic search, summarizing, not really embedding it deeply.
• 11:24
  Speaker 0: So the real potential is still untapped.
• 11:26
  Speaker 1: That's his view.
• 11:27
  Speaker 1: He thinks the big gains will come from fusion with other tech making AI almost invisible in the stack.
• 11:32
  Speaker 1: Yeah, got a ways to go
• 11:33
  Speaker 0: make sense.
• 11:34
  Speaker 0: There's hype and then there's deep integration.
• 11:36
  Speaker 1: right which brings us neatly to Governance legal policy.
• 11:41
  Speaker 1: This is where the conversation about responsibility really heats up the guardrails.
• 11:45
  Speaker 1: Absolutely
• 11:45
  Speaker 0: crucial.
• 11:46
  Speaker 0: And the big one here, mentioned by both Dr.
• 11:48
  Speaker 0: Nils Rower and Mirot Dermis, is the EU AI
• 11:51
  Speaker 1: Act.
• 11:51
  Speaker 1: Because of its global reach.
• 11:53
  Speaker 1: Right.
• 11:53
  Speaker 0: Exactly.
• 11:54
  Speaker 0: Its extraterritorial effect means businesses pretty much everywhere need to pay attention.
• 11:59
  Speaker 0: It's becoming the benchmark, the de facto global standard.
• 12:03
  Speaker 1: Huge implications for compliance worldwide.
• 12:05
  Speaker 0: Definitely.
• 12:06
  Speaker 0: And underpinning all that, Michael Charles Borelli stressed the need for solid data governance and record keeping.
• 12:12
  Speaker 1: Audit-ready AI programs.
• 12:13
  Speaker 0: Yeah.
• 12:14
  Speaker 0: You need that traceability.
• 12:16
  Speaker 0: Proof the system does what you say it does and behaves ethically.
• 12:19
  Speaker 1: Can't just let it run wild.
• 12:21
  Speaker 0: No way!
• 12:22
  Speaker 0: Which ties into copyright too.
• 12:23
  Speaker 0: Dr.
• 12:24
  Speaker 0: Barry Scannell reported on that massive anthropic settlement.
• 12:27
  Speaker 1: A one point five billion dollar one?
• 12:29
  Speaker 1: for using pirated books.
• 12:31
  Speaker 0: That's the one.
• 12:31
  Speaker 0: It basically put a concrete price on creative works used for training AI, signals a big shift towards structured licensing, pay upfront, basically.
• 12:39
  Speaker 1: Shipper than court.
• 12:40
  Speaker 1: Yeah.
• 12:40
  Speaker 1: Pretty
• 12:40
  Speaker 0: much.
• 12:41
  Speaker 0: And Jan Bernordeman noted that AIPPI, the Intellectual Property Association, is looking at global rules for AI and copyright, harmonization, fair pay for creators.
• 12:50
  Speaker 0: Important
• 12:50
  Speaker 1: work.
• 12:51
  Speaker 1: And beyond legal, Matthew Kay introduced his AI standards prompt map.
• 12:56
  Speaker 0: Integrating AI with global standards like ISO.
• 12:58
  Speaker 1: Yeah, for HR, IT, finance, making sure AI outputs are compliant, repeatable, scalable, building operational excellence.
• 13:07
  Speaker 0: Smart.
• 13:08
  Speaker 0: Ties it back to existing best practices.
• 13:09
  Speaker 1: And Giuseppe Stigliano had that wonderful analogy.
• 13:12
  Speaker 1: Raise AI like you would raise a child.
• 13:15
  Speaker 0: Meaning.
• 13:16
  Speaker 1: Meaning that early guidance values, mindset, attitude is critical for its ethical development, socially, politically, economically.
• 13:24
  Speaker 1: How we shape it now matters immensely.
• 13:27
  Speaker 0: Profound point.
• 13:28
  Speaker 0: It needs ethical foundations from the start.
• 13:30
  Speaker 1: Exactly.
• 13:31
  Speaker 1: So, okay, let's get into those foundations.
• 13:32
  Speaker 1: Data, infrastructure, MLO memes, the plumbing behind it all.
• 13:37
  Speaker 0: The unsung heroes, yeah.
• 13:39
  Speaker 0: And Ellie Gareffa's point comes back here.
• 13:41
  Speaker 0: Good AI content.
• 13:43
  Speaker 0: It's all about the training data, the references.
• 13:45
  Speaker 1: And retrieval data labeling.
• 13:46
  Speaker 1: You need that infrastructure at scale.
• 13:47
  Speaker 0: You do.
• 13:48
  Speaker 0: But Damian Millay added a really crucial nuance.
• 13:51
  Speaker 0: Improving AI results isn't just about better models or cleaner data.
• 13:55
  Speaker 0: What else
• 13:55
  Speaker 1: then?
• 13:55
  Speaker 0: It's often about refining the process, the human-AI interaction, the guardrails.
• 14:00
  Speaker 0: He shared an example where a big mistake was caught because the process failed safe, not because the model was perfect.
• 14:05
  Speaker 1: That's powerful.
• 14:06
  Speaker 1: Process over perfection.
• 14:08
  Speaker 0: Right.
• 14:08
  Speaker 0: And architecturally, Dr.
• 14:09
  Speaker 0: Sebastian Ronecki suggested we ditch the old AI onion model.
• 14:13
  Speaker 1: For something more practical.
• 14:14
  Speaker 1: Yeah.
• 14:15
  Speaker 0: He proposed two modes.
• 14:16
  Speaker 0: machine learning mode, optimizing specific outcomes from structured data, and AI mode, developing broad capabilities for unstructured stuff.
• 14:24
  Speaker 0: Helps make smarter investment and design choices.
• 14:27
  Speaker 1: More practical for building things out.
• 14:28
  Speaker 1: Definitely.
• 14:29
  Speaker 0: And we saw advanced infrastructure in action with Prem Narina's demo.
• 14:33
  Speaker 1: Use the Grock LPUs, those super fast chips.
• 14:36
  Speaker 0: Yeah, with Humane and Katonic AI.
• 14:38
  Speaker 0: real-time workflow automation.
• 14:40
  Speaker 0: Turning conversations straight into JIRA tickets, he said, intent is now programmable.
• 14:45
  Speaker 1: Wow, shows that seamless integration.
• 14:47
  Speaker 0: Exactly.
• 14:48
  Speaker 1: So it really underscores that robust infrastructure choices aren't just about speed.
• 14:53
  Speaker 1: They're fundamental for performance, security, compliance,
• 14:58
  Speaker 0: all of it.
• 14:58
  Speaker 0: And as Shalini Rao pointed out, you need that AI-ready data and governance baked in right from the start.
• 15:04
  Speaker 0: Okay,
• 15:04
  Speaker 1: let's shift gears one last time to the human element.
• 15:07
  Speaker 1: workforce, skills, leadership.
• 15:09
  Speaker 1: How is AI reshaping all of that?
• 15:11
  Speaker 0: Well, leadership is definitely changing.
• 15:14
  Speaker 0: Frederick De Bruyck was clear.
• 15:15
  Speaker 0: AI and leadership is non-negotiable
• 15:17
  Speaker 1: now.
• 15:17
  Speaker 1: Non-negotiable.
• 15:18
  Speaker 1: Yeah.
• 15:19
  Speaker 0: Leaders need that blend of empathy and smart data insights to stay relevant.
• 15:23
  Speaker 0: It's about building trust, not just, you know, ticking AI boxes.
• 15:26
  Speaker 1: Right.
• 15:27
  Speaker 1: And Gustavo Valbuena added that AI isn't just a side topic in leadership discussions anymore.
• 15:32
  Speaker 0: It's central.
• 15:32
  Speaker 1: Integral.
• 15:33
  Speaker 1: Focusing on maximizing benefits for everyone, the organization and the employees.
• 15:38
  Speaker 1: Support, productivity, better experience.
• 15:41
  Speaker 0: That's a positive framing.
• 15:42
  Speaker 1: It is.
• 15:43
  Speaker 1: And HR's role here is just massive.
• 15:46
  Speaker 1: Alana Brickner, drawing on Service Now's playbook, talked about HR becoming AI enablers.
• 15:51
  Speaker 0: AI enablers meaning.
• 15:52
  Speaker 1: Reinvesting the time AI frees up, building a culture of transparency, tackling that huge skills agenda.
• 15:57
  Speaker 1: A skills
• 15:57
  Speaker 0: gap is huge, right?
• 15:59
  Speaker 0: What was the stats?
• 16:00
  Speaker 1: Sixty percent of workers needing reskilling by twenty thirty.
• 16:03
  Speaker 1: Sixty percent.
• 16:04
  Speaker 0: Oh, that's urgent.
• 16:05
  Speaker 0: Extremely.
• 16:06
  Speaker 1: And David Green curated resources on actually deploying AI in HR, reinventing performance management for this new reality.
• 16:14
  Speaker 0: Of course, this inevitably brings up job displacement concerns.
• 16:17
  Speaker 0: Felicity Menzies raised a really interesting point about entry-level roles.
• 16:21
  Speaker 1: What was your concern?
• 16:22
  Speaker 0: That AI displacing those roles threatens the whole talent pipeline.
• 16:27
  Speaker 0: You lose that foundational learning ground.
• 16:29
  Speaker 0: It creates a delayed feedback problem.
• 16:31
  Speaker 0: efficiency now, but knowledge gaps later.
• 16:34
  Speaker 1: That's a really thoughtful point.
• 16:35
  Speaker 1: The long-term impact.
• 16:36
  Speaker 0: Yeah.
• 16:37
  Speaker 0: On the flip side... Pascal Burnett and Joanna Masijuska argued AI should take the mundane tasks.
• 16:42
  Speaker 1: To free us up from more creative work.
• 16:44
  Speaker 1: Exactly.
• 16:45
  Speaker 0: But they also warned about AI obesity.
• 16:48
  Speaker 0: Getting lazy and letting the AI do everything.
• 16:51
  Speaker 0: Huh.
• 16:51
  Speaker 1: AI obesity.
• 16:52
  Speaker 1: Need to watch out for that.
• 16:53
  Speaker 0: We do.
• 16:54
  Speaker 0: And Tim Evans talked about AI in education.
• 16:57
  Speaker 0: Going beyond just summarizing text, using it with things like Bloom's taxonomy for deeper transformative learning.
• 17:02
  Speaker 1: Empowering educators and students, not just automating tasks.
• 17:06
  Speaker 0: Precisely.
• 17:07
  Speaker 1: And the whole human-AI relationship is still unfolding.
• 17:10
  Speaker 1: Bernard Morris chat with Ameca, the humanoid robot.
• 17:13
  Speaker 0: Yeah, raise those big questions.
• 17:14
  Speaker 0: Is it authentic connection or just assistance?
• 17:18
  Speaker 0: What are the ethics as they become part of daily life?
• 17:21
  Speaker 1: Deep questions.
• 17:22
  Speaker 1: But Georgina Morris had a more grounded hot take.
• 17:25
  Speaker 1: Oh, yeah.
• 17:25
  Speaker 1: She argued, AI won't replace us soon because it lacks true creativity.
• 17:30
  Speaker 1: It relies on past data, human curiosity, specialized insight.
• 17:35
  Speaker 1: that's still irreplaceable.
• 17:36
  Speaker 0: A good reminder of unique human value.
• 17:38
  Speaker 1: Definitely.
• 17:40
  Speaker 1: Okay, let's wrap up the insights by looking at the market.
• 17:42
  Speaker 1: Sentiment, investment, what's the vibe out there?
• 17:45
  Speaker 0: Well, James Gosling and Eric Vesto both kind of sounded a cautionary note, drawing parallels to past tech bubbles like VR.
• 17:53
  Speaker 1: Seeing the hype is ahead of reality.
• 17:54
  Speaker 0: Pretty much.
• 17:55
  Speaker 0: They acknowledged AI tech is valuable, but the hype, way ahead of sensible outcomes, lots of startups they weren't, are probably doomed to lose.
• 18:04
  Speaker 0: It is.
• 18:05
  Speaker 0: And Dr.
• 18:06
  Speaker 0: Jeffrey Funk echoed that, comparing the spending on AI talent, those huge salaries to the dot-com era.
• 18:11
  Speaker 1: Questioning the actual commercial return.
• 18:13
  Speaker 1: Yeah,
• 18:14
  Speaker 0: from G-Wiz technology that can't be trusted, as he put it.
• 18:17
  Speaker 0: But Craig Skroggy offered a bit more balance.
• 18:20
  Speaker 0: He observed that AI hype and AI reality can coexist.
• 18:25
  Speaker 0: Quoting Altman and Gates, we overestimate the short-term, underestimate the long-term, his advice, long-term discipline in investing.
• 18:33
  Speaker 1: Makes sense.
• 18:34
  Speaker 1: Don't get swept away, but don't ignore the potential either.
• 18:36
  Speaker 0: Exactly.
• 18:37
  Speaker 0: And in this whole environment, Cassie Kozierkoff asked that killer leadership question about accountability.
• 18:42
  Speaker 1: When you build on foundation models you didn't create.
• 18:44
  Speaker 0: Right.
• 18:44
  Speaker 0: Who's accountable for the outputs?
• 18:46
  Speaker 0: Her answer.
• 18:47
  Speaker 0: The leaders deploying the AI.
• 18:49
  Speaker 0: you can't outsource all accountability.
• 18:51
  Speaker 0: That's
• 18:51
  Speaker 1: a crucial takeaway.
• 18:52
  Speaker 1: The buck stops with the Deployer.
• 18:54
  Speaker 2: If you enjoyed this deep dive, new deep dives drop every two weeks.
• 18:57
  Speaker 2: Also check out our other editions on ICT and tech, digital products and services, cloud and sustainability and green ICT.
• 19:03
  Speaker 2: So as we've kind of journeyed through this incredible AI momentum, I mean, from self-correcting agents, managing workflows all the way to potentially an AI made cancer vaccine.
• 19:14
  Speaker 2: It feels like one question really stands out for everyone, shaping this future.
• 19:17
  Speaker 2: Are we, you know, actively designing the guardrails, the ethical foundations for these incredibly powerful systems, or are we just sort of reacting?
• 19:26
  Speaker 2: Reacting to how fast they're evolving and just, well, trusting they'll grow upright all on their own.
• 19:30
  Speaker 2: Something to think about.
• 19:31
  Speaker 2: Thank you for joining us for this deep dive into the latest AI insights.
• 19:35
  Speaker 2: Make sure you subscribe so you don't miss our next deep dive and continue shaping the future with us.